A possibilistic solution to configure a battery closed-loop supply chain: Multi-objective approach

Tosarkani, Babak Mohamadpour; Amin, Saman Hassanzadeh

doi:10.1016/j.eswa.2017.09.039

Cited by 97 publications

(39 citation statements)

References 29 publications

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“…Nondominated sorting genetic algorithm (NSGA-II) was used to solve the deterministic mixed-integer nonlinear programming model. Tosarkani and Amin [30] studied the establishment and application of fully fuzzy programming (FFP) method to determine the possible upper, middle, and lower profit ranges of a multicomponent, multiproduct, and multiperiod battery closed-loop supply chain in the case of inaccurate information. Moreover, the problem was extended to multiobjective considering green factors.…”

Section: Multiperiod and Multiproductmentioning

confidence: 99%

Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment

Wang

2020

Mathematical Problems in Engineering

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This paper studies a supply chain network design model with price competition. The supply chain provides multiple products for a market area in multiple periods. The model considers the location of manufacturers and retailers and assumes a probabilistic customer behavior based on an attraction function depending on both the location and the quality of the retailers. We aim to design the supply chain under the capacity constraint and maximize the supply chain profit in the competitive environment. The problem is formulated as a mixed integer nonlinear programming model. To solve the problem, we propose two heuristic algorithms—Simulated Annealing Search (SA) and Particle Swarm Optimization (PSO)—and numerically demonstrate the effectiveness of the proposed algorithms. Through the sensitivity analysis, we give some management insights.

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Section: Multiperiod and Multiproductmentioning

confidence: 99%

Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment

Wang

2020

Mathematical Problems in Engineering

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“…Tsao et al used fuzzy probabilistic multi-objective programing to model their problem [44]. Tosarkani and Amin applied a fully fuzzy programming method is used to address the uncertainty [43]. Haddadsisakht and Ryan carried out a study with the premise of stochastic demand uncertainty [18].…”

Section: Uncertainty In Supply Chainsmentioning

confidence: 99%

“…Green supply chain is a management approach that seeks to minimize the environmental and environmental impacts of products and services and social collections. Also, green Supply Chain Management is an integrated supply chain of green purchases from suppliers to manufacturing, customer delivery and reverse logistics [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]18,19,[21][22][23][26][27][28][29][30][31][32][34][35][36][37][38][39][40][41][42][43][44][45]. In addition, the idea of green supply chain management is to eliminate or minimizes waste (energy, greenhouse gas, chemical/hazardous emissions).…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy multi-objective programming approach to develop a green closed-loop supply chain network design problem under uncertainty: Modifications of imperialist competitive algorithm

Fakhrzad

Goodarzian

2019

RAIRO-Oper. Res.

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The last decade has seen a numerous studies focusing on the closed-loop supply chain. Accordingly, the uncertainty conditions as well as the green emissions of facilities are still open issues. In this paper, a new fuzzy multi-objective programming approach is to present for a production-distribution model in order to develop a multi-product, multi-period and multi-level green closed-loop supply chain network problem, which this model is formulated as multi-objective mixed linear integer programming (MOMILP). In regards to offered fuzzy multi-objective model, three conflicting goals are exited, simultaneously. The objective functions are to minimizing the total cost, minimizing the gas emissions costs due to vehicle movements between centers, and maximizing the reliability of delivery demand due to the reliability of the suppliers. To get closer to real-world applications, the parameters of model are considered by fuzzy numbers. Another novelty of proposed model is in the solution methodology. To solve the model, this study not only uses a well-known Imperialist Competitive Algorithm (ICA) but a number of new modifications of ICA (MICA) also have been provided to address the proposed problem, which is to demonstrate the efficiency and performance of the proposed algorithm with other algorithms included: SA, ICA, ACO, GA, and PSO are compare. Finally, different analyses with a variety of problem complexity in different sizes are performed to assess the performance of algorithms as well as some sensitivity analyses on the efficiency of model are studied.

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“…Recovery activities are performed on returned products. These recovery activities include the acquisition of used products, reverse logistics, product disposition, repair or remanufacturing, remarketing, and recycling [26,43,52]. The goal of RL is to gain economic and environmental values from returned products; however, the aim of forward (traditional) logistics is to provide products for customers [2].…”

Section: Introductionmentioning

confidence: 99%

A perspective on the reverse logistics of plastic pallets in Canada

Amin

Karaphillis

2018

Jnl Remanufactur

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A possibilistic solution to configure a battery closed-loop supply chain: Multi-objective approach

Cited by 97 publications

References 29 publications

Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment

Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment

A Fuzzy multi-objective programming approach to develop a green closed-loop supply chain network design problem under uncertainty: Modifications of imperialist competitive algorithm

A perspective on the reverse logistics of plastic pallets in Canada

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